The pan-immune-inflammation value and systemic immune-inflammation index in advanced melanoma patients under immunotherapy

The prognostic role of pan-immune inflammation value in patients with metastatic castration resistance prostate cancer treated with Lutetium-177 (177Lu)-PSMA-617

BACKGROUND

Pan-immune inflammation value (PIV) is a newly defined biomarker that includes whole cellular components that are indicators of systemic inflammation in complete blood count (CBC), easily accessible and has the potential to reflect both the body's immune response and systemic inflammation status. This study evaluated the pretreatment PIV for its prognostic impact on overall survival (OS) in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with Lutetium-177 (177Lu)-PSMA-617.

METHODS

The PIV was based on the earliest CBC obtained within 1 month before treatment initiation. Patients were categorized into low and high PIV groups based on the median pretreatment PIV, and the relationship between OS and PIV groups was assessed by multivariable analysis.

RESULTS

A total of 43 patients with mCRPC treated with (177Lu)-PSMA-617 were included. The median OS was longer in the low PIV group (15.1 months [95% confidence interval [CI] 10.6-19.5]) than in the high PIV group (4.2 months [95% CI 1.7-6.6]) (p < 0.001). In multivariable analysis, high PIV (hazard ratio [HR]: 4.3, 95% CI 1.194-15.93, p = 0.026) and high Eastern Cooperative Oncology Group performance score (HR: 7.05, 95% CI 1.48-33.46, p = 0.014) were associated with shorter OS.

CONCLUSION

This study showed that pretreatment PIV might be a prognostic factor in patients with mCRPC treated with (177Lu)-PSMA-617.

Systemic immune-inflammation index values are associated with non-melanoma skin cancers: evidence from the National Health and Nutrition Examination Survey 2010-2018

Introduction

The systemic immune-inflammation index (SII), based on peripheral lymphocyte, neutrophil, and platelet counts, has recently been investigated as a prognostic marker in several tumors. However, the SII has rarely been reported in skin cancers. In this study, we aimed to assess the association between SII values and the risk of occurrence of skin cancers.

Material and methods

This cross-sectional study was based on National Health and Nutrition Examination Survey data from 2010 to 2018 and involved 32,012 participants. The SII was calculated as the platelet count × neutrophil count/lymphocyte count. A weighted multivariate logistic analysis was conducted to examine the relationship between SII values and the occurrence of skin cancers. In addition, a subgroup analysis and a sensitivity analysis were conducted to identify underlying moderators and the stability of the relationship, respectively.

Results

Compared with participants in the lowest quartile of SII values, the odds ratios for non-melanoma skin cancer were 1.650 (95% CI: 1.158-2.352) for participants in the quartile with the highest SII values after multivariate adjustments. In subgroup analyses, we found significant interactions between log-transformed SII values and age (p < 0.001 for interaction), race (p < 0.001 for interaction), education level (p < 0.001 for interaction), marital status (p < 0.001 for interaction), and annual household incomes (p < 0.001 for interaction) in the association with non-melanoma skin cancer.

Conclusions

Our findings suggest a positive association between high SII values and skin cancers in the U.S. population. Age, levels of education, marital status, and annual household incomes affect the positive association between high SII values and non-melanoma skin cancers.

The Construction of a Nomogram Using the Pan-Immune-Inflammation Value Combined with a PILE Score for Immunotherapy Prediction Prognosis in Advanced NSCLC

Purpose

The purpose of this study was to investigate the predictive value of Pan-Immune-Inflammation Value (PIV) combined with the PILE score for immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) and to construct a nomogram prediction model to provide reference for clinical work.

Patients and Methods

Patients with advanced NSCLC who received ICIs treatment in Qingdao Municipal Hospital from January 2019 to December 2021 were selected as the study subjects. The chi-square test, Kaplan-Meier survival analysis, and Cox proportional risk regression analysis were used to evaluate the prognosis. The results were visualized by a nomogram, and the performance of the model was judged by indicators such as the area under the subject operating characteristic curve (AUC) and C-index. The patients were divided into high- and low-risk groups by PILE score, and the prognosis of patients in different risk groups was evaluated.

Results

Multivariate Cox regression analysis showed that immune-related adverse events (irAEs) were prognostic factors for overall survival (OS) improvement, and ECOG PS score ≥2, bone metastases before treatment, and high PIV expression were independent risk factors for OS. The C index of OS predicted by the nomogram model is 0.750 (95% CI: 0.677-0.823), and the Calibration and ROC curves show that the model has good prediction performance. Compared with the low-risk group, patients in the high-risk group of PILE were associated with a higher inflammatory state and poorer physical condition, which often resulted in a poorer prognosis.

Conclusion

PIV can be used as a prognostic indicator for patients with advanced NSCLC treated with ICIs, and a nomogram prediction model can be constructed to evaluate the survival prediction of patients, thus contributing to better clinical decision-making and prognosis assessment.

Novel pretreatment nomograms based on pan-immune-inflammation value for predicting clinical outcome in patients with head and neck squamous cell carcinoma

Background

The prognostic value of an effective biomarker, pan-immune-inflammation value (PIV), for head and neck squamous cell carcinoma (HNSCC) patients after radical surgery or chemoradiotherapy has not been well explored. This study aimed to construct and validate nomograms based on PIV to predict survival outcomes of HNSCC patients.

Methods

A total of 161 HNSCC patients who underwent radical surgery were enrolled retrospectively for development cohort. The cutoff of PIV was determined using the maximally selected rank statistics method. Multivariable Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to develop two nomograms (Model A and Model B) that predict disease-free survival (DFS). The concordance index, receiver operating characteristic curves, calibration curves, and decision curve analysis were used to evaluate the nomograms. A cohort composed of 50 patients who received radiotherapy or chemoradiotherapy (RT/CRT) alone was applied for generality testing of PIV and nomograms.

Results

Patients with higher PIV (≥123.3) experienced a worse DFS (HR, 5.01; 95% CI, 3.25-7.72; p<0.0001) and overall survival (OS) (HR, 5.23; 95% CI, 3.34-8.18; p<0.0001) compared to patients with lower PIV (<123.3) in the development cohort. Predictors of Model A included age, TNM stage, neutrophil-to-lymphocyte ratio (NLR), and PIV, and that of Model B included TNM stage, lymphocyte-to-monocyte ratio (LMR), and PIV. In comparison with TNM stage alone, the two nomograms demonstrated good calibration and discrimination and showed satisfactory clinical utility in internal validation. The generality testing results showed that higher PIV was also associated with worse survival outcomes in the RT/CRT cohort and the possibility that the two nomograms may have a universal applicability for patients with different treatments.

Conclusions

The nomograms based on PIV, a simple but useful indicator, can provide prognosis prediction of individual HNSCC patients after radical surgery and may be broadly applicated for patients after RT/CRT alone.

Evaluation of hematological inflammatory parameters in patients with palmoplantar pustulosis

BACKGROUND

Palmoplantar pustulosis (PPP) is a chronic inflammatory disease of ill-defined etiopathology. Recent studies have proposed complete blood count-based hematological parameters, such as neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR), as biomarkers to monitor disease status in many inflammatory diseases. This study aimed to analyze for the first time the clinical significance of hematological parameters, including NLR, monocyte/lymphocyte ratio (MLR), PLR, mean platelet volume (MPV), plateletcrit (PCT), and pan-immune-inflammation value (PIV) in PPP patients.

METHODS

We retrospectively investigated the clinical and laboratory data of 237 patients with PPP and 250 sex-age-matched healthy controls (HCs). Hematological parameters were compared between patients with PPP and HCs. The correlations between these parameters and disease severity, as well as treatment response, were analyzed.

RESULTS

NLR, MLR, MPV, PCT, and PIV values were significantly higher in PPP patients than in HCs. But in receiver-operating characteristic analyses, only monocyte count (Youden Index = 0.53), PCT (Youden Index = 0.65), and PIV (Youden Index = 0.52) performed relatively accurate distinguishment between moderate-to-severe cases and mild cases. PCT and PIV values were significantly correlated with disease severity. After treatment, both PIV and PCT values decreased significantly in the responder group but not in the non-responder group.

CONCLUSIONS

Hematological parameters altered significantly in PPP patients. PCT and PIV can be used as simple and inexpensive biomarkers for systemic inflammation in PPP patients.

Baseline Serum neutrophil-to-lymphocyte ratio in acral melanoma compared with nonacral melanoma and its prognostic significance

BACKGROUND

Acral lentiginous melanoma (ALM), a cutaneous melanoma subtype, exhibits a poorer prognosis than nonacral cutaneous melanoma (NACM). The neutrophil-to-lymphocyte ratio (NLR) is emerging as a prognostic indicator across diverse cancers.

OBJECTIVE

We explored the baseline NLR disparities between ALM and NACM, and the NLR's prognostic significance in patients with ALM.

METHODS

We reviewed records of patients with ALM and NACM diagnosed between 1997 and 2022, analyzing medical data.

RESULTS

Among 327 and 159 patients with ALM and NACM, respectively, baseline NLR varied based on distinct clinicopathologic factors between ALM and NACM. In stage 3 to 4 melanomas, the median NLR for ALM (2.18; IQR, 1.70-3.08) significantly surpassed NACM (1.74; IQR, 1.33-2.53) (P = .029). In patients with ALM, high NLR (hazard ratio, 1.64; 95% CI, 1.02-2.66; P = .043) was independently correlated with poor progression-free survival when adjusting for ulceration, Breslow thickness of ≥2 mm, and nodal invasion.

LIMITATIONS

Single-center, retrospective design.

CONCLUSION

Advanced-stage ALM exhibited a significantly higher baseline NLR compared with that of NACM. Evaluating baseline NLR could provide valuable prognostic insights for patients with ALM.

The relationship between disease activity with pan-immune-inflammatory value and systemic immune-inflammation index in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic, systemic inflammatory disease. Immune system cells have an important role in RA. Our aim was to investigate the relationship between disease activity, systemic immune-inflammation index (SII), and pan-immune-inflammation value (PIV) levels in RA patients. We planned to investigate whether these 2 measurements have an advantage over each other. About 67 patients diagnosed with RA and 49 healthy controls included in this study. RA was diagnosed based on 2010 ACR classification criteria. In this cross-sectional study, peripheral blood tests, C-reactive protein (CRP), hemogram, and erythrocyte sedimentation rate levels were noted after the physical examination of all participants. PIV was calculated with the formula: (neutrophil count × platelet count × monocyte count) / lymphocyte count. SII was calculated as follows: (neutrophil count × monocytes count) / lymphocyte count. The disease activity score 28 (DAS28) were noted in patients with RA. CRP values of active RA group were significantly higher than remission RA and control groups (P < .001), control and remission RA groups were similar (P = .86). PIV and SII are significantly higher in active RA than remission RA and control (P < .001, P < .001) higher in remission RA than control (P < .001, P < .001). Receiver operating characteristic curve analysis in predicting remission compared to the control group, CRP was not significant, PIV and SII was significant and PIV has higher sensitivity and sensitivity, a PIV value of > 217.31 have sensitivity 75.0% and specificity 85.7%. CRP, PIV, and SII are statistically significant in predicting active RA compared to the remission RA and control group. Our findings show that PIV, and SII are easy, inexpensive and reliable markers predicting remission in RA patients. CRP was not significant compared to remission RA and control group, PIV and SII was significant and PIV has higher sensitivity and specificity than SII in the remission group in RA. Patients with high disease activity, PIV, SII, and CRP levels were effective in showing disease activity compared to RA remission group and healthy controls.

Exploring long-term responses to immune checkpoint inhibitors in recurrent and metastatic head and neck squamous cell carcinoma

OBJECTIVES

Immune checkpoint inhibitors (ICI) have introduced a new era in the treatment of recurrent and/or metastatic head and neck squamous cell carcinoma (R/M HNSCC). Optimal duration for ICI therapy is still unclear and the long-term outcomes and toxicity in patients responding to these therapies warrant further exploration. This study attempts to identify the clinical and biological determinants of a durable response and evaluate outcomes following ICI treatment discontinuation.

MATERIALS AND METHODS

A retrospective review of 181 patients treated with ICI for R/M HNSCC was conducted. Long-term responders were defined as patients who sustained disease control at least two years after initiating ICI therapy. We compared clinical and biological characteristics associated with these long-term responders against the broader treatment population.

RESULTS

10 % of R/M HNSCC patients treated with ICIs demonstrated a durable long-term response. Only three relapses (16 %) occurred after discontinuing ICI treatment in this subset, with a median follow-up of 52 months. Upon retreatment with ICI, two attained a documented response. Extended ICI response was observed even with < 2 years of treatment. 74 % of long-term responders experienced immune-related adverse events (irAEs), 37 % of which severe irAEs. Hypothyroidism was the most frequently reported irAEs. The predictive potential of systemic inflammation indices for clinical response appears to be limited.

CONCLUSIONS

ICI present an optimistic avenue for HNSCC patients, offering substantial long-term responses. The study suggests that a two-year treatment could be optimal and irAEs, although common, are typically mild.

Intratumoural and systemic inflammation as predictors for treatment response in BRAF-mutated melanoma patients under targeted therapies

Intratumoural as well as systemic inflammation in melanoma has thoroughly been studied in the context of patients treated with immune checkpoint inhibitors but not with BRAF/MEK inhibitors (BRAFi/MEKi). We aimed to study whether parameters of intratumoral and systemic inflammation correlate with clinical outcome in patients with BRAF-mutant metastatic melanoma treated with BRAFi/MEKi. We studied 51 CM patients with unresectable stage III or IV who had the indication for BRAFi/MEKi treatment based on confirmed BRAF mutation. Baseline systemic immune-inflammation markers such as the systemic immune-inflammation index (SII) and the expression of intratumoral inflammation markers such as COX-2 protein expression were correlated with clinical outcome measures. On multivariable analyses, lower intratumoral COX-2 expression (OR 33.9, 95% CI 3.2-356.8) and lower SII (OR 6.3, 95% CI 1.1-34.8) proved to be significant independent predictors for objective response to targeted therapy. Elevated S100B (HR 1.2, 95% CI 1.03-1.3) was a significant predictor for progressive disease. Moreover, elevated S100B (HR 1.37, 95% CI 1.14-1.65) and LDH (HR 1.002, 95% CI 1.0001-1.003) were significant independent predictors for melanoma-specific death. In conclusion, the present study indicates that low SII values and low intratumoral COX-2 protein expression are significant independent predictors for treatment response to BRAFi/MEKi.

Unveiling the link between systemic inflammation markers and cognitive performance among older adults in the US: A population-based study using NHANES 2011-2014 data

PURPOSE

This study aimed to evaluate the association between systemic inflammation markers and cognitive performance among older US adults.

METHODS

This cross-sectional study assessed 3,632 older participants from the 2011-2014 National Health and Nutrition Examination Survey (NHANES). The main analysis included participants aged over 60 years. Systemic inflammation markers were quantified by calculating the composite inflammation indicators from the blood routine count, and cognitive performance was assessed using Consortium to Establish a Registry for Alzheimer's Disease (CERAD) test, Animal Fluency test (AFT), and Digit Symbol Substitution test (DSST).

RESULTS

There were 2,743 individuals enrolled in the current analysis. The overall mean age was 64.9 years and 48.7 % were males. The levels of SIRI and PIV were significant negative associated with scores of CERAD, CERAD delayed recall, and DSST in the unadjusted models. Moreover, SII were significant negative associated with scores of CERAD and CERAD delayed recall. After adjusting the covariates of demographics, lifestyle factors, history of chronic diseases and BMI, significant negative association were observed between systematic inflammation markers and cognitive performance. Additionally, a progressive and significant decrease in the score of cognitive performance assessments with the increased levels of SIRI, SII, and PIV were respectively observed. Finally, the correlation between systemic inflammation markers and cognitive performance were evidenced in the sensitive analysis.

CONCLUSION

Findings support a strong inverse correlation between systemic inflammation markers and cognitive performance, suggesting that addressing inflammation could be a promising avenue for enhancing cognitive health and mitigating age-related cognitive decline.

Pretreatment Pan-Immune-Inflammation Value (PIV) in Predicting Therapeutic Response and Clinical Outcomes of Neoadjuvant Immunochemotherapy for Esophageal Squamous Cell Carcinoma

PURPOSE

The pan-immune-inflammation value (PIV), which reflects the balance between the host immune and inflammatory status, is a readily available index for evaluating cancer outcomes. Until now, however, no study has demonstrated the clinical response of PIV to neoadjuvant immunochemotherapy (NICT) in esophageal squamous cell carcinoma (ESCC).

METHODS

This retrospective study included 218 patients with ESCC who underwent NICT. The relationship between PIV and therapeutic response (pathological complete response [PCR]) and clinical outcomes (overall survival [OS] and disease-free survival [DFS]) was examined. Cox proportional, hazard-regression analyses and the Kaplan-Meier method were used for survival analyses. Recursive partitioning analysis (RPA) was used to establish a novel risk stratification model.

RESULTS

Sixty-six patients (30.3%) achieved PCR after NICT. Using PCR as the endpoint of interest, patients were compared in groups based on the optimal threshold. PIV was closely related to PCR (odds ratio [OR] 0.311, 95% confidence interval [CI] 0.140-0.690, P = 0.004). Compared with patients in the low PIV cohort, patients with high PIV had worse 3-year OS (58.7% vs. 83.6%, P < 0.001) and DFS (51.9% vs. 79.1%, P < 0.001). PIV was an independent predictor of OS (hazard ratio [HR] 2.364, 95% CI 1.183-4.724, P = 0.015) and DFS (HR 1.729, 95% CI 1.026-2.913, P = 0.040). Three risk groups with varied DFS and OS were staged by using an RPA method, and the prognostication accuracy was considerably improved.

CONCLUSIONS

Pretreatment PIV can predict the therapeutic efficacy of NICT for ESCC. Because of better prognostic stratification, pretreatment PIV is a novel, sensitive, and effective indicator in ESCC receiving NICT. The prognostic results of PIV need to be verified in additional prospective studies.

Using peripheral immune-inflammatory blood markers in tumors treated with immune checkpoint inhibitors: An INVIDIa-2 study sub-analysis

The neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammatory index (SII) have been reported as prognosticators in non-small cell lung cancer (NSCLC), renal cell carcinoma (RCC), and melanoma. This analysis of the INVIDIa-2 study on influenza vaccination in patients with cancer treated with immune checkpoint inhibitors (ICIs) assessed NLR and SII on overall survival (OS) by literature-reported (LR), receiver operating characteristic curve (ROC)-derived (ROC) cutoffs or as continuous variable (CV). NLR and SII with ROC cutoffs of <3.4 (p < 0.001) and <831 (p < 0.001) were independent factors for OS in multivariate analysis. SII with LR, ROC, or CV significantly predicted OS in NSCLC (p = 0.002, p = 0.003, p = 0.003), RCC (p = 0.034, p = 0.014, p = 0.014), and melanoma (p = 0.038, p = 0.022, p = 0.019). NLR with LR and ROC cutoffs predicted OS in first line (p < 0.001 for both) and second line or beyond (p = 0.006 for both); likewise SII (p < 0.001; p = 0.002 and p < 0.001). NLR and SII are prognosticators in NSCLC, RCC, and melanoma treated with ICIs.

Prognostic significance of the pretreatment pan-immune-inflammation value in cancer patients: an updated meta-analysis of 30 studies

Background

The pan-immune-inflammation value (PIV) has been reported as a promising prognostic biomarker in multiple cancers but still remains inconclusive. The objective of this study is to systematically investigate the association of the pretreatment PIV with survival outcomes in cancer patients, based on available literature.

Methods

Online databases including PubMed, Embase and the Web of Science were thoroughly searched for studies evaluating the prognostic role of the pretreatment PIV in cancers from the inception to June 2023. Hazard ratios (HRs) with 95% confidence intervals (CIs) were always assessed using a random-effects model. Statistical analyses were performed using Stata 12.0.

Results

Thirty studies were finally included after comprehensively study searching. In total, 8,799 cancer patients were enrolled in this meta-analysis. The pooled results demonstrated that patients in the high PIV group had a significantly poorer overall survival (HR = 2.07; 95%CI: 1.77-2.41; I2 = 73.0%) and progression-free survival (HR = 1.83; 95%CI: 1.37-2.45; I2 = 98.2%) than patients in the low PIV group. The prognostic significance of the PIV score on overall survival and progression-free survival was observed across various geographical regions, tumor stages and treatment strategies. Sensitivity analyses supported the stability of the above combined results.

Conclusion

This meta-analysis demonstrated that the pretreatment PIV could be a non-invasive and efficacious prognostic biomarker for cancer patients.

The prognostic impact of inflammation in patients with decompensated acute heart failure, as assessed using the pan-immune inflammation value (PIV)

There is increasing evidence that composite scores based on blood counts, which are reflectors of uncontrolled inflammation in the development and progression of heart failure, can be used as prognostic biomarkers in heart failure patients. The prognostic effects of pan-immune inflammation (PIV) as an independent predictor of in-hospital mortality in patients with acute heart failure (AHF) were evaluated based on this evidence. The data of 640 consecutive patients hospitalized for New York Heart Association (NYHA) class 2-3-4 AHF with reduced ejection fraction were analyzed and 565 patients were included after exclusion. The primary outcome was in hospital all-cause death. Secondary outcomes were defined as the following in-hospital events: Acute kidney injury (AKI), malignant arrhythmias, acute renal failure (ARF) and stroke. The PIV was computed using hemogram parameters such as lymphocytes, neutrophils, monocytes and platelets. Patients were categorized as low or high PIV group according to the median value, which was 382.8. A total of 81 (14.3%) in-hospital deaths, 31 (5.4%) AKI, 34 (6%) malignant arrhythmias, 60 (10.6%) ARF and 11 (2%) strokes were reported. Patients with high PIV had a higher in-hospital mortality rate than patients with low PIV (OR: 1.51, 95% CI, 1.26-1.80, p < 0.001). Incorporating PIV into the full model significantly improved model performance (odds ratio X2, p < 0.001) compared to the baseline model constructed with other inflammatory markers. PIV is a potent predictor of prognosis with better performance than other well-known inflammatory markers for patients with AHF.

Clinical utility of preoperative pan-immune-inflammation value (PIV) for prognostication in patients with esophageal squamous cell carcinoma

BACKGROUND

Several researches have shown that pan-immune-inflammation value (PIV) is related to cancer prognosis in recent years. In esophageal squamous cell carcinoma (ESCC), nevertheless, the prognostic impact of PIV remains unclear. The present study sought to investigate the prognostic impact of preoperative PIV in ESCC with radical resection.

METHODS

The data of 294 ESCC patients who received radical resection were retrospectively analyzed. Based on analyzing the non-linear relationship between PIV and cancer-specific survival (CSS), the optimal cutoff value for PIV was calculated by the restricted cubic spline (RCS) model. Cox proportional hazards regression was carried out to identify the prognostic factors. A risk stratification model was established by recursive partitioning analysis (RPA). The performance of the RPA-based model was assessed by the decision curve analysis (DCA) and receiver operating characteristic (ROC).

RESULTS

The RCS visualized the non-linear relationship between PIV and CSS (P < 0.0001). Then patients were then divided into high and low groups based on the optimal threshold of 308.2. The 5-year CSS (17.7 % vs. 48.3 %, P < 0.001) was significantly worse in patients with high PIV than those in the low group. Subgroup analyses confirmed that patients with low PIV also achieved better 5-year survival at different pathological tumor node metastasis (pTNM) stages (pTNM I: P = 0.022; pTNM II: P = 0.001; pTNM III: P = 0.011). PIV served as an independent prognostic factor of CSS (hazard ratio = 1.983, P < 0.001). A new staging involving three risk groups with significantly different CSS was developed using RPA algorithms based on pTNM and PIV. Compared with the pTNM classification, the RPA-based model exhibited significantly superior performance for prognostication.

CONCLUSION

The present study confirmed the prognostic impact of PIV in ESCC who treated with radical resection. PIV was associated with the tumor stage and prognosis, which might be useful in the preoperative assessment of ESCC.

Prognostic Performance of Inflammatory Biomarkers Based on Complete Blood Counts in COVID-19 Patients

With the end of the pandemic, COVID-19 has entered an endemic phase with expected seasonal spikes. Consequently, the implementation of easily accessible prognostic biomarkers for patients with COVID-19 remains an important area of research. In this monocentric study at a German tertiary care hospital, we determined the prognostic performance of different clinical and blood-based parameters in 412 COVID-19 patients. We evaluated the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), pan-immune-inflammation value (PIV), and absolute eosinopenia (AEP, 0/µL) of COVID-19 patients (n = 412). The Siddiqui and Mehra staging proposal, the WHO clinical progression scale, and COVID-19-associated death were used as COVID-19 outcome measures. With respect to Siddiqi and Mehra staging, patient age of older than 75 years, high C-reactive protein (CRP), absolute eosinopenia (AEP), cardiovascular comorbidities, and high ferritin were significant independent predictors for severe COVID-19. When outcome was determined according to the WHO clinical progression scale, patient age of older than 75 years, high CRP, high LDH, AEP, high neutrophil-to-lymphocyte ratio (NLR), and the presence of pulmonal comorbidities were significant independent predictors for severe COVID-19. Finally, COVID-19-associated death was predicted independently by patient age of older than 75 years, high LDH, high NLR, and AEP. Eosinopenia (< 40/µL) was observed in 74.5% of patients, and AEP in almost 45%. In conclusion, the present real-world data indicate that the NLR is superior to more complex systemic immune-inflammation biomarkers (e.g., SII and PIV) in COVID-19 prognostication. A decreased eosinophil count emerged as a potential hallmark of COVID-19 infection, whereas AEP turned out to be an accessible independent biomarker for COVID-19 severity and mortality.

Predictive value of prognostic nutritional and systemic immune-inflammation indices for patients with microsatellite instability-high metastatic colorectal cancer receiving immunotherapy

Background

The prognostic nutritional index (PNI) and systemic immune-inflammation index (SII) are indicators of nutritional immune status. They have been reported associated with clinical outcomes of various solid tumors. However, it is unclear whether they can serve as predictors for patients with microsatellite instability-high (MSI-H) metastatic colorectal cancer (mCRC) receiving immunotherapy. Our objective was to study the prognostic value of PNI and SII in these patients.

Methods

Seventy-five MSI-H mCRC patients were enrolled in our study. Logistic regression analysis was used to identify features that influenced immunotherapy response. Survival differences between groups of mCRC patients were compared using the Kaplan-Meier method and log-rank test. The independent risk parameters for progression-free survival (PFS) and overall survival (OS) of patients with MSI-H mCRC were established by Cox proportional risk regression analysis.

Results

The optimal SII and PNI cutoff values were 409.6 and 51.35. Higher PNI (p = 0.012) and lower high-density lipoprotein cholesterol (HDLC, p = 0.012) were associated with a better immunotherapy response. SII (p = 0.031), cholesterol (CHO) (p = 0.007) and aspartate aminotransferase (AST) (p = 0.031) were independent prognostic factors correlated with OS. Higher PNI (p = 0.012) and lower AST (p = 0.049) were negative predictors of PFS. In addition, patients suffered from immune-related adverse events (irAEs) had a lower SII level (p = 0.04).

Conclusion

Higher AST and SII, and lower PNI predict worse outcomes in MSI-H mCRC patients undergoing immunotherapy. Moreover, patients with lower SII before immunotherapy suffered from irAEs more often.

Prognostic role of the pretreatment systemic immune-inflammation index in patients with glioma: A meta-analysis

Background

The systemic immune-inflammation index (SII) has been recognized as the indicator that reflects the status of immune responses. The SII is related to the prognostic outcome of many malignancies, whereas its role in gliomas is controversial. For patients with glioma, we, therefore, conducted a meta-analysis to determine if the SII has a prognostic value.

Methods

Studies relevant to this topic were searched from 16 October 2022 in several databases. In patients with glioma, the relation of the SII level with the patient prognosis was analyzed based on hazard ratios (HRs) as well as corresponding 95% confidence intervals (CIs). Moreover, subgroup analysis was conducted to examine a possible heterogeneity source.

Results

There were eight articles involving 1,426 cases enrolled in the present meta-analysis. The increased SII level predicted the dismal overall survival (OS) (HR = 1.81, 95% CI = 1.55–2.12, p &lt; 0.001) of glioma cases. Furthermore, an increased SII level also predicted the prognosis of progression-free survival (PFS) (HR = 1.87, 95% CI = 1.44–2.43, p &lt; 0.001) in gliomas. An increased SII was significantly associated with a Ki-67 index of ≥30% (OR = 1.72, 95% CI = 1.10–2.69, p = 0.017). However, a high SII was not correlated with gender (OR = 1.05, 95% CI = 0.78–1.41, p = 0.734), KPS score (OR = 0.64, 95% CI = 0.17–2.37, p = 0.505), or symptom duration (OR 1.22, 95% CI 0.37–4.06, p = 0.745).

Conclusion

There was a significant relation between an increased SII level with poor OS and the PFS of glioma cases. Moreover, patients with glioma with a high SII value have a positive relationship with a Ki-67 of ≥30%.

Biomarkers for Outcome in Metastatic Melanoma in First Line Treatment with Immune Checkpoint Inhibitors

Introduction: A high proportion of metastatic melanoma patients do not respond to immune checkpoint inhibitors (ICI), and until now, no validated biomarkers for response and survival have been known. Methods: We performed a retrospective analysis of outcomes in patients with metastatic melanoma treated with first-line ICI at the Institute of Oncology Ljubljana from January 2018 to December 2020. The immune-related adverse events (irAEs) and serum immune-inflammation parameters (neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (LR), systemic immune-inflammation index (SII) and pan-immune-inflammation value (PIV)) were analyzed as potential biomarkers for response and survival. Survival rates were calculated using the Kaplan–Meier method and then compared with the log-rank test. Multivariate regression Cox analysis was used to determine independent prognostic factors for progression-free survival (PFS) and overall survival (OS). Results: Median follow-up was 22.5 months. The estimated median progression-free survival (PFS) was 15 months (95% CI 3.3–26.2). The two-year survival rate (OS) was 66.6%. Among 129 treated patients, 24 (18.6%) achieved complete response, 28 (21.7%) achieved partial response, 26 (20.2%) had stable disease and 51 (39.5%) patients experienced a progressive disease. There was a higher response rate in patients with irAEs (p < 0.001) and high NLR before the second cycle of ICI (p = 0.052). Independent prognostic factors for PFS were irAE (HR 0.41 (95% CI 0.23–0.71)), SII before the first cycle of ICI (HR 1.94 (95% CI 1.09–3.45)) and PLR before the second cycle of ICI (HR 1.71 (95% CI 1.03–2.83)). The only independent prognostic factor for OS was SII before the first cycle of ICI (HR 2.60 (95% CI 0.91–7.50)). Conclusions: Patients with high pre-treatment levels of SII had a higher risk of progression and death; however, patients with irAEs in the high-SII group might respond well to ICI. Patients who develop irAEs and have high NLRs before the second ICI application have higher rates of CR and PR, which implicates their use as early biomarkers for responsiveness to ICI.

Body Composition and Metabolic Dysfunction Really Matter for the Achievement of Better Outcomes in High-Grade Serous Ovarian Cancer

Although obesity-associated metabolic disorders have a negative impact on various cancers, such evidence remains controversial for ovarian cancer. Here, we aimed to evaluate the impact of body composition (BC) and metabolism disorders on outcomes in high-grade serous ovarian cancer (HGSOC).

METHODS

We analyzed clinical/genomic data from two cohorts (PUC n = 123/TCGA-OV n = 415). BC was estimated using the measurement of adiposity/muscle mass by a CT scan. A list of 425 genes linked to obesity/lipid metabolism was used to cluster patients using non-negative matrix factorization. Differential expression, gene set enrichment analyses, and Ecotyper were performed. Survival curves and Cox-regression models were also built-up.

RESULTS

We identified four BC types and two clusters that, unlike BMI, effectively correlate with survival. High adiposity and sarcopenia were associated with worse outcomes. We also found that recovery of a normal BC and drug interventions to correct metabolism disorders had a positive impact on outcomes. Additionally, we showed that immune-cell-depleted microenvironments predominate in HGSOC, which was more evident among the BC types and the obesity/lipid metabolism cluster with worse prognosis.

CONCLUSIONS

We have demonstrated the relevance of BC and metabolism disorders as determinants of outcomes in HGSOC. We have shone a spotlight on the relevance of incorporating corrective measures addressing these disorders to obtain better results.

Discovering the Clinical and Prognostic Role of Pan-Immune-Inflammation Values on Oral Cavity Squamous Cell Carcinoma

A newly introduced pan-immune-inflammation value (PIV) was not evaluated for its role in oral cavity squamous cell carcinoma (OSCC). In this study, the PIV was calculated with the following equation (neutrophil count × platelet count × monocyte count)/lymphocyte count from the results of the automated hematology analyzers in 853 OSCC patients from 2005 to 2017. The optimal cutoff for the preoperative PIV was 268, as determined by a receiver operating characteristic curve. Significant differences were observed for alcohol consumption, smoking, pT status, pN status, overall pathological status, extranodal extension, cell differentiation, depth of invasion, and perineural invasion between higher and lower PIV patients (all p values < 0.05). Kaplan-Meier and univariate regression analyses indicated that higher PIV was associated with worse overall survival, disease-free survival, locoregional recurrence-free survival, and distant metastasis-free survival (all p values < 0.001). Multivariate analyses adjusted by various factors further demonstrated that PIV was an independent prognostic factor for overall and distant metastasis-free survival (p = 0.027, HR: 1.281 and p = 0.031, HR: 1.274, respectively). In conclusion, a higher PIV level was associated with poor clinicopathological factors in OSCC patients and could be used to predict poor posttreatment outcomes, especially for overall and distant metastasis-free survival.

Prognostic value of pan-immune-inflammation value in colorectal cancer patients: A systematic review and meta-analysis

Background

The pan-immune-inflammation value (PIV) has been reported as a novel prognostic biomarker in multiple malignancies. The aim of this study is to investigate the prognostic value of the PIV in patients with colorectal cancer.

Methods

We comprehensively searched electronic databases including PubMed, Embase and Web of Science up to August 2022. The endpoints were survival outcomes. Hazard ratios (HRs) with 95% confidence intervals (CIs) for survival data were collected for analysis.

Results

Six studies including 1879 participants were included. A significant heterogeneity in the PIV cut-off value among studies was observed. The combined results indicated that patients in the high baseline PIV group had a worse overall survival (HR=2.09; 95%CI: 1.67-2.61; P<0.0001; I2 = 7%) and progression-free survival (HR=1.82; 95%CI: 1.49-2.22; P<0.0001; I2 = 15%). In addition, early PIV increase after treatment initiation was significantly associated with decreased overall survival (HR=1.79; 95%CI: 1.13-2.93; P=0.01; I2 = 26%), and a trend toward poor progression-free survival (HR=2.00; 95%CI: 0.90-4.41; P=0.09; I2 = 70%).

Conclusion

Based on existing evidence, the PIV could act as a valuable prognostic index in patients with colorectal cancer. However, the heterogeneity in the PIV cut-off value among studies should be considered when interpreting these findings.

Prognostic Potential of the Baseline Pan-Immune-Inflammation Value and Neutrophil/Lymphocyte Ratio in Stage I to III Melanoma Patients

Prognostic biomarkers derived from complete blood count (CBC) have received marked interest as an indirect measure of the inflammatory pressure in cancers such as metastatic melanoma. Here, we evaluated the novel pan-immune-inflammation value (PIV) and the frequently assessed neutrophil/lymphocyte ratio (NLR) in a large cohort of patients with cutaneous melanoma (CM) without distant metastases (stages I to III). PIV and NLR were calculated at CM diagnosis. Healthy controls were also included. We used the Kaplan-Meier method to estimate crude survival probabilities and used Cox proportional hazards regression for multiple adjustment of hazard ratios. We observed that higher PIV (HR: 1.72, 95% CI 1.14 to 2.58 and HR: 1.696, 95% CI 1.029 to 2.795, respectively) and NLR (HR: 1.70, 95% CI 1.10 to 2.62) values were associated with CM relapse and CM-specific death in the crude analysis. However, when adjusting for potential confounders, in particular age and tumor thickness, the total effect of PIV and NLR on CM-relapse-free (HR: 1.28, 95% CI 0.83 to 1.98 and HR: 1.26, 95% CI 0.80 to 1.98, respectively) and CM-specific survival (HR: 1.36, 95% CI 0.80 to 2.30 and HR: 1.37, 95% CI 0.80 to 2.33, respectively) was substantially reduced. However, both PIV and NLR were positively correlated with age and tumor thickness, which are important independent predictors for CM relapse and CM-specific death. In conclusion, in stage I to III CM patients PIV as well as NLR appear to be confounded by age and tumor thickness and probably have no potential to further improve the prediction of survival of stage I to III CM patients beyond standard prognostic factors.

Global Trends in Research of NF-κB in Melanoma from 2000 to 2021: A Study of Bibliometric Analysis

In the pathogenesis of melanoma, NF-κB is a key signaling pathway. Appling bibliometric analysis, we identify the frontiers and hotspots about NF-κB in melanoma, as well as distinguishing features of scientific research and output all over the world during the past 22 years. 2226 publications published from 2000 to 2021 and related information were retrieved based on Science Citation Index Expanded (SCI-expanded) of Web of Science Core Collection (WoSCC). VOSviewer and Citespace were used to analyze bibliometric indicators and visualize the hotspots and research trend of studies on NF-κB in melanoma. The results indicated that despite fluctuations, the number of publications (Np) related to the research of NF-κB in melanoma per year increased over the past 22 years. The USA had the most publications. H-index and the number of citations (Nc) of the USA were also in the first place. PloS One was the most productive journal, and League of European Research Universities (LERU) was the most productive affiliation. Recently, the keywords “NF-kappa-b,” “melanoma,” “apoptosis,” “expression,” “activation,” “cancer,” and “metastasis” appeared most frequently. Our study suggested that articles associated with NF-κB in melanoma tend to increase. In this field, the USA was an influential country and a big producer. Most publications focused on clinical and basic research in the past 22 years, and keywords “tumor necrosis factor” and “trail induced apoptosis” had the highest burst strength.

The Association between the Pan-Immune-Inflammation Value and Cancer Prognosis: A Systematic Review and Meta-Analysis

Background: Prognostic scores derived from the blood count have garnered significant interest as an indirect measure of the inflammatory pressure in cancer. The recently developed pan-immune-inflammation value (PIV), an equation including the neutrophil, platelet, monocyte, and lymphocyte levels, has been evaluated in several cohorts, although with variations in the tumor types, disease stages, cut-offs, and treatments. Therefore, we evaluated the association between survival and PIV in cancer, performing a systematic review and meta-analysis. Methods: We conducted a systematic review from the Pubmed, Medline, and Embase databases to filter the published studies until 17 May 2022. The meta-analyses were performed with the generic inverse-variance method with a random-effects model. Results: Fifteen studies encompassing 4942 patients were included. In the pooled analysis of fifteen studies, the patients with higher PIV levels had significantly increased risk of death than those with lower PIV levels (HR: 2.00, 95% CI: 1.51−2.64, p < 0.001) and increased risk of progression or death (HR: 1.80, 95% CI: 1.39−2.32, p < 0.001). Analyses were consistent across several clinical scenarios, including non-metastatic or metastatic disease, different cut-offs (500, 400, and 300), and treatment with targeted therapy or immunotherapy (p < 0.001 for each). Conclusion: The available evidence demonstrates that PIV could be a prognostic biomarker in cancer. However, further research is needed to explore the promise of PIV as a prognostic biomarker in patients with non-metastatic disease or patients treated without immunotherapy or targeted therapy.

The relationship between pan-immune-inflammation value and survival outcomes in patients with metastatic renal cell carcinoma treated with nivolumab in the second line and beyond: a Turkish oncology group kidney cancer consortium (TKCC) study

BACKGROUND

Pan-immune-inflammation value (PIV) is an easily accessible immune marker based on peripheral blood to estimate prognosis in patients with cancer. This study evaluates the prognostic value of PIV in patients with metastatic renal cell carcinoma (mRCC) treated with nivolumab.

METHODS

In this retrospective cohort study, patients with mRCC treated with nivolumab in the second line and beyond were selected from the Turkish Oncology Group Kidney Cancer Consortium (TKCC) database. PIV was calculated using the following formula: neutrophil (10³/mm³) x monocyte (10³/mm³) x platelet (10³/mm³)/lymphocyte (10³/mm³).

RESULTS

A total of 152 patients with mRCC were included in this study. According to cut-off value for PIV, 77 (50.7%) and 75 (49.3%) patients fell into PIV-low ([Formula: see text] 372) and PIV-high (> 372) groups, respectively. In multivariate analysis, PIV-high (HR: 1.64, 95% CI 1.04-2.58, p = 0.033 for overall survival (OS); HR: 1.55, 95% CI 1.02-2.38, p = 0.042 for progression-free survival (PFS)) was independent risk factor for OS and PFS after adjusting for confounding variables, such as performance score, the International mRCC Database Consortium (IMDC) risk score, and liver metastasis.

CONCLUSION

This study established that pre-treatment PIV might be a prognostic biomarker in patients with mRCC treated with nivolumab in the second line and beyond.